{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import time\n",
    "\n",
    "from datasets import dataset_utils\n",
    "\n",
    "# Main slim library\n",
    "from tensorflow.contrib import slim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert the dataset to TFRecords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset files already exist. Exiting without re-creating them.\n"
     ]
    }
   ],
   "source": [
    "from datasets import convert_insulators\n",
    "convert_insulators.run('/workspace/JiaXuejian')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download the Inception V1 checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> Downloading inception_v1_2016_08_28.tar.gz 100.0%\n",
      "Successfully downloaded inception_v1_2016_08_28.tar.gz 24642554 bytes.\n"
     ]
    }
   ],
   "source": [
    "from datasets import dataset_utils\n",
    "\n",
    "url = \"http://download.tensorflow.org/models/inception_v1_2016_08_28.tar.gz\"\n",
    "checkpoints_dir = '/tmp/checkpoints'\n",
    "\n",
    "if not tf.gfile.Exists(checkpoints_dir):\n",
    "    tf.gfile.MakeDirs(checkpoints_dir)\n",
    "\n",
    "dataset_utils.download_and_uncompress_tarball(url, checkpoints_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Apply Pre-trained Inception V1 model to Images.\n",
    "\n",
    "We have to convert each image to the size expected by the model checkpoint.\n",
    "There is no easy way to determine this size from the checkpoint itself.\n",
    "So we use a preprocessor to enforce this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from /tmp/checkpoints/inception_v1.ckpt\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Probability 45.14% => [cocker spaniel, English cocker spaniel, cocker]\n",
      "Probability 21.55% => [Sussex spaniel]\n",
      "Probability 10.37% => [Irish setter, red setter]\n",
      "Probability 5.06% => [Welsh springer spaniel]\n",
      "Probability 2.99% => [clumber, clumber spaniel]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import tensorflow as tf\n",
    "\n",
    "try:\n",
    "    import urllib2 as urllib\n",
    "except ImportError:\n",
    "    import urllib.request as urllib\n",
    "\n",
    "from datasets import imagenet\n",
    "from nets import inception\n",
    "from preprocessing import inception_preprocessing\n",
    "\n",
    "from tensorflow.contrib import slim\n",
    "\n",
    "image_size = inception.inception_v1.default_image_size\n",
    "\n",
    "with tf.Graph().as_default():\n",
    "    url = 'https://upload.wikimedia.org/wikipedia/commons/7/70/EnglishCockerSpaniel_simon.jpg'\n",
    "    image_string = urllib.urlopen(url).read()\n",
    "    image = tf.image.decode_jpeg(image_string, channels=3)\n",
    "    processed_image = inception_preprocessing.preprocess_image(image, image_size, image_size, is_training=False)\n",
    "    processed_images  = tf.expand_dims(processed_image, 0)\n",
    "    \n",
    "    # Create the model, use the default arg scope to configure the batch norm parameters.\n",
    "    with slim.arg_scope(inception.inception_v1_arg_scope()):\n",
    "        logits, _ = inception.inception_v1(processed_images, num_classes=1001, is_training=False)\n",
    "    probabilities = tf.nn.softmax(logits)\n",
    "    \n",
    "    init_fn = slim.assign_from_checkpoint_fn(\n",
    "        os.path.join(checkpoints_dir, 'inception_v1.ckpt'),\n",
    "        slim.get_model_variables('InceptionV1'))\n",
    "    \n",
    "    with tf.Session() as sess:\n",
    "        init_fn(sess)\n",
    "        np_image, probabilities = sess.run([image, probabilities])\n",
    "        probabilities = probabilities[0, 0:]\n",
    "        sorted_inds = [i[0] for i in sorted(enumerate(-probabilities), key=lambda x:x[1])]\n",
    "        \n",
    "    plt.figure()\n",
    "    plt.imshow(np_image.astype(np.uint8))\n",
    "    plt.axis('off')\n",
    "    plt.show()\n",
    "\n",
    "    names = imagenet.create_readable_names_for_imagenet_labels()\n",
    "    for i in range(5):\n",
    "        index = sorted_inds[i]\n",
    "        print('Probability %0.2f%% => [%s]' % (probabilities[index] * 100, names[index]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fine-tune the model on a different set of labels.\n",
    "\n",
    "We will fine tune the inception model on the Flowers dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from preprocessing import inception_preprocessing\n",
    "import tensorflow as tf\n",
    "\n",
    "from tensorflow.contrib import slim\n",
    "\n",
    "\n",
    "def load_batch(dataset, batch_size=32, height=299, width=299, is_training=False):\n",
    "    \"\"\"Loads a single batch of data.\n",
    "    \n",
    "    Args:\n",
    "      dataset: The dataset to load.\n",
    "      batch_size: The number of images in the batch.\n",
    "      height: The size of each image after preprocessing.\n",
    "      width: The size of each image after preprocessing.\n",
    "      is_training: Whether or not we're currently training or evaluating.\n",
    "    \n",
    "    Returns:\n",
    "      images: A Tensor of size [batch_size, height, width, 3], image samples that have been preprocessed.\n",
    "      images_raw: A Tensor of size [batch_size, height, width, 3], image samples that can be used for visualization.\n",
    "      labels: A Tensor of size [batch_size], whose values range between 0 and dataset.num_classes.\n",
    "    \"\"\"\n",
    "    data_provider = slim.dataset_data_provider.DatasetDataProvider(\n",
    "        dataset, common_queue_capacity=32,\n",
    "        common_queue_min=8)\n",
    "    image_raw, label = data_provider.get(['image', 'label'])\n",
    "    \n",
    "    # Preprocess image for usage by Inception.\n",
    "    image = inception_preprocessing.preprocess_image(image_raw, height, width, is_training=is_training)\n",
    "    \n",
    "    # Preprocess the image for display purposes.\n",
    "    image_raw = tf.expand_dims(image_raw, 0)\n",
    "    image_raw = tf.image.resize_images(image_raw, [height, width])\n",
    "    image_raw = tf.squeeze(image_raw)\n",
    "\n",
    "    # Batch it up.\n",
    "    images, images_raw, labels = tf.train.batch(\n",
    "          [image, image_raw, label],\n",
    "          batch_size=batch_size,\n",
    "          num_threads=1,\n",
    "          capacity=2 * batch_size)\n",
    "    \n",
    "    return images, images_raw, labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-6-e8e87a2c60cf>:47: softmax_cross_entropy (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.softmax_cross_entropy instead. Note that the order of the logits and labels arguments has been changed.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:398: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "\n",
      "Future major versions of TensorFlow will allow gradients to flow\n",
      "into the labels input on backprop by default.\n",
      "\n",
      "See @{tf.nn.softmax_cross_entropy_with_logits_v2}.\n",
      "\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:399: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.compute_weighted_loss instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:147: add_arg_scope.<locals>.func_with_args (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.add_loss instead.\n",
      "WARNING:tensorflow:From <ipython-input-6-e8e87a2c60cf>:48: get_total_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.get_total_loss instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:258: get_losses (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.get_losses instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:260: get_regularization_losses (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n",
      "Instructions for updating:\n",
      "Use tf.losses.get_regularization_losses instead.\n",
      "INFO:tensorflow:Summary name losses/Total Loss is illegal; using losses/Total_Loss instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/slim/python/slim/learning.py:737: Supervisor.__init__ (from tensorflow.python.training.supervisor) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please switch to tf.train.MonitoredTrainingSession\n",
      "INFO:tensorflow:Restoring parameters from /tmp/checkpoints/inception_v1.ckpt\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Starting Session.\n",
      "INFO:tensorflow:Saving checkpoint to path /tmp/inception_finetuned1/model.ckpt\n",
      "INFO:tensorflow:Starting Queues.\n",
      "INFO:tensorflow:global_step/sec: 0\n",
      "INFO:tensorflow:Recording summary at step 0.\n",
      "INFO:tensorflow:global step 0: loss = 1.0671 (6.233 sec/step)\n",
      "INFO:tensorflow:global step 1: loss = 1.2698 (1.855 sec/step)\n",
      "INFO:tensorflow:global step 2: loss = 3.2829 (1.623 sec/step)\n",
      "INFO:tensorflow:global step 3: loss = 4.5438 (1.631 sec/step)\n",
      "INFO:tensorflow:global step 4: loss = 1.1758 (1.866 sec/step)\n",
      "INFO:tensorflow:global step 5: loss = 1.1531 (1.610 sec/step)\n",
      "INFO:tensorflow:global step 6: loss = 0.9893 (1.756 sec/step)\n",
      "INFO:tensorflow:global step 7: loss = 1.3152 (2.194 sec/step)\n",
      "INFO:tensorflow:global step 8: loss = 1.0762 (1.927 sec/step)\n",
      "INFO:tensorflow:global step 9: loss = 0.9939 (1.586 sec/step)\n",
      "INFO:tensorflow:global step 10: loss = 1.1228 (2.061 sec/step)\n",
      "INFO:tensorflow:global step 11: loss = 1.0613 (1.680 sec/step)\n",
      "INFO:tensorflow:global step 12: loss = 1.1279 (1.813 sec/step)\n",
      "INFO:tensorflow:global step 13: loss = 1.1644 (1.842 sec/step)\n",
      "INFO:tensorflow:global step 14: loss = 1.3929 (2.201 sec/step)\n",
      "INFO:tensorflow:global step 15: loss = 1.0032 (1.597 sec/step)\n",
      "INFO:tensorflow:global step 16: loss = 1.0953 (1.723 sec/step)\n",
      "INFO:tensorflow:global step 17: loss = 1.0739 (1.604 sec/step)\n",
      "INFO:tensorflow:global step 18: loss = 1.1142 (1.614 sec/step)\n",
      "INFO:tensorflow:global step 19: loss = 1.1029 (2.071 sec/step)\n",
      "INFO:tensorflow:global step 20: loss = 1.1070 (1.787 sec/step)\n",
      "INFO:tensorflow:global step 21: loss = 1.0389 (2.372 sec/step)\n",
      "INFO:tensorflow:global step 22: loss = 1.0938 (1.731 sec/step)\n",
      "INFO:tensorflow:global step 23: loss = 1.1026 (1.809 sec/step)\n",
      "INFO:tensorflow:global step 24: loss = 1.0624 (1.470 sec/step)\n",
      "INFO:tensorflow:global step 25: loss = 1.0724 (1.645 sec/step)\n",
      "INFO:tensorflow:global step 26: loss = 1.2228 (1.814 sec/step)\n",
      "INFO:tensorflow:global step 27: loss = 1.1180 (1.575 sec/step)\n",
      "INFO:tensorflow:global step 28: loss = 1.0004 (1.992 sec/step)\n",
      "INFO:tensorflow:global step 29: loss = 1.0727 (1.892 sec/step)\n",
      "INFO:tensorflow:global step 30: loss = 1.0004 (2.188 sec/step)\n",
      "INFO:tensorflow:global step 31: loss = 0.9932 (1.675 sec/step)\n",
      "INFO:tensorflow:global step 32: loss = 0.9537 (1.902 sec/step)\n",
      "INFO:tensorflow:global step 33: loss = 0.9680 (1.944 sec/step)\n",
      "INFO:tensorflow:global step 34: loss = 1.1854 (1.658 sec/step)\n",
      "INFO:tensorflow:global step 35: loss = 0.9428 (1.643 sec/step)\n",
      "INFO:tensorflow:global step 36: loss = 1.0336 (2.107 sec/step)\n",
      "INFO:tensorflow:global step 37: loss = 0.8226 (1.888 sec/step)\n",
      "INFO:tensorflow:global step 38: loss = 1.1496 (1.915 sec/step)\n",
      "INFO:tensorflow:global step 39: loss = 0.8273 (1.824 sec/step)\n",
      "INFO:tensorflow:global step 40: loss = 0.9569 (1.712 sec/step)\n",
      "INFO:tensorflow:global step 41: loss = 0.7998 (1.872 sec/step)\n",
      "INFO:tensorflow:global step 42: loss = 0.9329 (2.196 sec/step)\n",
      "INFO:tensorflow:global step 43: loss = 1.1564 (1.642 sec/step)\n",
      "INFO:tensorflow:global step 44: loss = 0.8665 (1.999 sec/step)\n",
      "INFO:tensorflow:global step 45: loss = 1.0375 (1.611 sec/step)\n",
      "INFO:tensorflow:global step 46: loss = 0.8308 (2.079 sec/step)\n",
      "INFO:tensorflow:global step 47: loss = 0.8215 (2.098 sec/step)\n",
      "INFO:tensorflow:global step 48: loss = 0.8410 (1.746 sec/step)\n",
      "INFO:tensorflow:global step 49: loss = 0.7633 (1.687 sec/step)\n",
      "INFO:tensorflow:global step 50: loss = 0.8586 (2.071 sec/step)\n",
      "INFO:tensorflow:global step 51: loss = 0.7579 (1.268 sec/step)\n",
      "INFO:tensorflow:global step 52: loss = 0.7267 (2.155 sec/step)\n",
      "INFO:tensorflow:global step 53: loss = 0.9359 (1.761 sec/step)\n",
      "INFO:tensorflow:global step 54: loss = 0.7211 (1.836 sec/step)\n",
      "INFO:tensorflow:global step 55: loss = 0.7502 (1.899 sec/step)\n",
      "INFO:tensorflow:global step 56: loss = 1.1430 (1.876 sec/step)\n",
      "INFO:tensorflow:global step 57: loss = 0.8518 (1.611 sec/step)\n",
      "INFO:tensorflow:global step 58: loss = 1.0092 (1.627 sec/step)\n",
      "INFO:tensorflow:global step 59: loss = 0.9294 (1.703 sec/step)\n",
      "INFO:tensorflow:global step 60: loss = 0.8972 (2.030 sec/step)\n",
      "INFO:tensorflow:global step 61: loss = 0.8755 (2.151 sec/step)\n",
      "INFO:tensorflow:global step 62: loss = 0.8464 (2.012 sec/step)\n",
      "INFO:tensorflow:global step 63: loss = 0.8883 (1.869 sec/step)\n",
      "INFO:tensorflow:global step 64: loss = 0.8651 (1.724 sec/step)\n",
      "INFO:tensorflow:global step 65: loss = 0.8454 (1.786 sec/step)\n",
      "INFO:tensorflow:global step 66: loss = 0.8928 (1.708 sec/step)\n",
      "INFO:tensorflow:global step 67: loss = 1.0134 (1.994 sec/step)\n",
      "INFO:tensorflow:global step 68: loss = 0.8611 (2.189 sec/step)\n",
      "INFO:tensorflow:global step 69: loss = 0.8141 (1.800 sec/step)\n",
      "INFO:tensorflow:global step 70: loss = 0.6349 (1.818 sec/step)\n",
      "INFO:tensorflow:global step 71: loss = 0.6309 (1.671 sec/step)\n",
      "INFO:tensorflow:global step 72: loss = 0.6049 (1.949 sec/step)\n",
      "INFO:tensorflow:global step 73: loss = 0.6077 (2.194 sec/step)\n",
      "INFO:tensorflow:global step 74: loss = 0.8526 (1.787 sec/step)\n",
      "INFO:tensorflow:global step 75: loss = 0.8043 (1.273 sec/step)\n",
      "INFO:tensorflow:global step 76: loss = 0.7300 (2.068 sec/step)\n",
      "INFO:tensorflow:global step 77: loss = 0.6401 (1.907 sec/step)\n",
      "INFO:tensorflow:global step 78: loss = 0.6378 (1.927 sec/step)\n",
      "INFO:tensorflow:global step 79: loss = 0.7398 (2.016 sec/step)\n",
      "INFO:tensorflow:global step 80: loss = 0.8827 (1.906 sec/step)\n",
      "INFO:tensorflow:global step 81: loss = 0.6131 (1.745 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 82: loss = 0.6835 (2.190 sec/step)\n",
      "INFO:tensorflow:global step 83: loss = 0.6978 (1.611 sec/step)\n",
      "INFO:tensorflow:global step 84: loss = 0.5607 (2.306 sec/step)\n",
      "INFO:tensorflow:global step 85: loss = 0.5906 (1.658 sec/step)\n",
      "INFO:tensorflow:global step 86: loss = 0.5745 (1.654 sec/step)\n",
      "INFO:tensorflow:global step 87: loss = 0.7204 (1.803 sec/step)\n",
      "INFO:tensorflow:global step 88: loss = 0.6022 (2.024 sec/step)\n",
      "INFO:tensorflow:global step 89: loss = 0.6282 (1.985 sec/step)\n",
      "INFO:tensorflow:global step 90: loss = 0.5569 (2.015 sec/step)\n",
      "INFO:tensorflow:global step 91: loss = 0.5540 (1.763 sec/step)\n",
      "INFO:tensorflow:global step 92: loss = 0.6130 (1.713 sec/step)\n",
      "INFO:tensorflow:global step 93: loss = 1.1404 (1.879 sec/step)\n",
      "INFO:tensorflow:global step 94: loss = 0.5746 (2.117 sec/step)\n",
      "INFO:tensorflow:global step 95: loss = 0.5851 (2.209 sec/step)\n",
      "INFO:tensorflow:global step 96: loss = 0.5802 (1.676 sec/step)\n",
      "INFO:tensorflow:global step 97: loss = 0.5236 (1.478 sec/step)\n",
      "INFO:tensorflow:global step 98: loss = 0.5932 (1.607 sec/step)\n",
      "INFO:tensorflow:global step 99: loss = 0.5289 (1.844 sec/step)\n",
      "INFO:tensorflow:global step 100: loss = 0.7562 (2.104 sec/step)\n",
      "INFO:tensorflow:global step 101: loss = 0.6288 (2.075 sec/step)\n",
      "INFO:tensorflow:global step 102: loss = 0.5308 (2.147 sec/step)\n",
      "INFO:tensorflow:global step 103: loss = 0.5299 (1.908 sec/step)\n",
      "INFO:tensorflow:global step 104: loss = 0.5930 (2.016 sec/step)\n",
      "INFO:tensorflow:global step 105: loss = 0.6355 (1.601 sec/step)\n",
      "INFO:tensorflow:global step 106: loss = 0.5510 (2.101 sec/step)\n",
      "INFO:tensorflow:global step 107: loss = 0.5078 (1.833 sec/step)\n",
      "INFO:tensorflow:global step 108: loss = 0.6590 (2.083 sec/step)\n",
      "INFO:tensorflow:global step 109: loss = 0.4963 (1.758 sec/step)\n",
      "INFO:tensorflow:global step 110: loss = 0.4970 (1.800 sec/step)\n",
      "INFO:tensorflow:global step 111: loss = 0.6348 (1.987 sec/step)\n",
      "INFO:tensorflow:global step 112: loss = 0.5166 (1.621 sec/step)\n",
      "INFO:tensorflow:global step 113: loss = 0.5051 (1.739 sec/step)\n",
      "INFO:tensorflow:global step 114: loss = 0.9546 (1.949 sec/step)\n",
      "INFO:tensorflow:global step 115: loss = 0.6297 (1.826 sec/step)\n",
      "INFO:tensorflow:global step 116: loss = 0.6878 (1.976 sec/step)\n",
      "INFO:tensorflow:global step 117: loss = 0.7571 (1.957 sec/step)\n",
      "INFO:tensorflow:global step 118: loss = 0.6702 (1.943 sec/step)\n",
      "INFO:tensorflow:global step 119: loss = 0.5219 (1.513 sec/step)\n",
      "INFO:tensorflow:global step 120: loss = 0.8396 (1.872 sec/step)\n",
      "INFO:tensorflow:global step 121: loss = 0.5498 (2.006 sec/step)\n",
      "INFO:tensorflow:global step 122: loss = 0.5982 (1.820 sec/step)\n",
      "INFO:tensorflow:global step 123: loss = 0.5874 (1.758 sec/step)\n",
      "INFO:tensorflow:global step 124: loss = 0.5539 (1.725 sec/step)\n",
      "INFO:tensorflow:global step 125: loss = 0.8406 (1.872 sec/step)\n",
      "INFO:tensorflow:global step 126: loss = 0.7760 (2.174 sec/step)\n",
      "INFO:tensorflow:global step 127: loss = 0.6295 (1.871 sec/step)\n",
      "INFO:tensorflow:global step 128: loss = 0.6123 (1.754 sec/step)\n",
      "INFO:tensorflow:global step 129: loss = 0.6200 (1.898 sec/step)\n",
      "INFO:tensorflow:global step 130: loss = 0.6134 (1.803 sec/step)\n",
      "INFO:tensorflow:global step 131: loss = 0.5664 (1.543 sec/step)\n",
      "INFO:tensorflow:global step 132: loss = 0.5892 (1.797 sec/step)\n",
      "INFO:tensorflow:global step 133: loss = 0.5599 (2.214 sec/step)\n",
      "INFO:tensorflow:global step 134: loss = 0.5258 (1.859 sec/step)\n",
      "INFO:tensorflow:global step 135: loss = 0.6250 (1.697 sec/step)\n",
      "INFO:tensorflow:global step 136: loss = 0.4791 (1.505 sec/step)\n",
      "INFO:tensorflow:global step 137: loss = 0.5503 (2.034 sec/step)\n",
      "INFO:tensorflow:global step 138: loss = 0.5230 (2.276 sec/step)\n",
      "INFO:tensorflow:global step 139: loss = 0.5456 (2.115 sec/step)\n",
      "INFO:tensorflow:global step 140: loss = 0.5043 (1.979 sec/step)\n",
      "INFO:tensorflow:global step 141: loss = 0.4909 (2.164 sec/step)\n",
      "INFO:tensorflow:global step 142: loss = 0.4879 (1.820 sec/step)\n",
      "INFO:tensorflow:global step 143: loss = 0.5330 (2.006 sec/step)\n",
      "INFO:tensorflow:global step 144: loss = 0.4952 (1.893 sec/step)\n",
      "INFO:tensorflow:global step 145: loss = 0.5115 (1.907 sec/step)\n",
      "INFO:tensorflow:global step 146: loss = 1.0440 (1.852 sec/step)\n",
      "INFO:tensorflow:global step 147: loss = 0.5773 (1.888 sec/step)\n",
      "INFO:tensorflow:global step 148: loss = 0.5320 (1.469 sec/step)\n",
      "INFO:tensorflow:global step 149: loss = 0.5575 (2.453 sec/step)\n",
      "INFO:tensorflow:global step 150: loss = 0.4909 (2.031 sec/step)\n",
      "INFO:tensorflow:global step 151: loss = 0.6565 (1.689 sec/step)\n",
      "INFO:tensorflow:global step 152: loss = 0.8321 (2.046 sec/step)\n",
      "INFO:tensorflow:global step 153: loss = 0.4975 (1.756 sec/step)\n",
      "INFO:tensorflow:global step 154: loss = 0.4820 (1.753 sec/step)\n",
      "INFO:tensorflow:global step 155: loss = 0.6727 (1.695 sec/step)\n",
      "INFO:tensorflow:global step 156: loss = 0.9771 (1.854 sec/step)\n",
      "INFO:tensorflow:global step 157: loss = 0.6030 (2.162 sec/step)\n",
      "INFO:tensorflow:global step 158: loss = 0.5073 (1.804 sec/step)\n",
      "INFO:tensorflow:global step 159: loss = 0.8088 (1.799 sec/step)\n",
      "INFO:tensorflow:global step 160: loss = 0.5641 (1.730 sec/step)\n",
      "INFO:tensorflow:global step 161: loss = 0.6019 (2.006 sec/step)\n",
      "INFO:tensorflow:global step 162: loss = 0.5312 (1.821 sec/step)\n",
      "INFO:tensorflow:global step 163: loss = 0.5109 (1.995 sec/step)\n",
      "INFO:tensorflow:global step 164: loss = 0.5369 (1.725 sec/step)\n",
      "INFO:tensorflow:global step 165: loss = 0.6458 (2.037 sec/step)\n",
      "INFO:tensorflow:global step 166: loss = 0.6437 (2.008 sec/step)\n",
      "INFO:tensorflow:global step 167: loss = 0.5318 (1.546 sec/step)\n",
      "INFO:tensorflow:global step 168: loss = 0.4835 (1.936 sec/step)\n",
      "INFO:tensorflow:global step 169: loss = 0.4831 (1.672 sec/step)\n",
      "INFO:tensorflow:global step 170: loss = 0.4937 (1.931 sec/step)\n",
      "INFO:tensorflow:global step 171: loss = 0.4824 (1.599 sec/step)\n",
      "INFO:tensorflow:global step 172: loss = 0.5548 (1.640 sec/step)\n",
      "INFO:tensorflow:global step 173: loss = 0.4618 (1.758 sec/step)\n",
      "INFO:tensorflow:global step 174: loss = 0.4673 (1.429 sec/step)\n",
      "INFO:tensorflow:global step 175: loss = 0.5012 (2.049 sec/step)\n",
      "INFO:tensorflow:global step 176: loss = 0.4695 (1.610 sec/step)\n",
      "INFO:tensorflow:global step 177: loss = 0.4424 (1.703 sec/step)\n",
      "INFO:tensorflow:global step 178: loss = 0.5854 (1.795 sec/step)\n",
      "INFO:tensorflow:global step 179: loss = 0.4408 (2.060 sec/step)\n",
      "INFO:tensorflow:global step 180: loss = 0.4487 (1.220 sec/step)\n",
      "INFO:tensorflow:global step 181: loss = 0.4558 (1.176 sec/step)\n",
      "INFO:tensorflow:global step 182: loss = 0.4579 (1.295 sec/step)\n",
      "INFO:tensorflow:global step 183: loss = 0.4828 (1.316 sec/step)\n",
      "INFO:tensorflow:global step 184: loss = 0.5978 (1.410 sec/step)\n",
      "INFO:tensorflow:global step 185: loss = 0.5009 (1.481 sec/step)\n",
      "INFO:tensorflow:global step 186: loss = 0.5494 (1.568 sec/step)\n",
      "INFO:tensorflow:global step 187: loss = 0.4510 (1.437 sec/step)\n",
      "INFO:tensorflow:global step 188: loss = 0.5056 (1.229 sec/step)\n",
      "INFO:tensorflow:global step 189: loss = 0.4650 (1.228 sec/step)\n",
      "INFO:tensorflow:global step 190: loss = 0.4399 (1.302 sec/step)\n",
      "INFO:tensorflow:global step 191: loss = 0.5061 (0.994 sec/step)\n",
      "INFO:tensorflow:global step 192: loss = 0.4813 (1.220 sec/step)\n",
      "INFO:tensorflow:global step 193: loss = 0.5530 (1.120 sec/step)\n",
      "INFO:tensorflow:global step 194: loss = 0.8330 (1.730 sec/step)\n",
      "INFO:tensorflow:global step 195: loss = 0.5572 (1.492 sec/step)\n",
      "INFO:tensorflow:global step 196: loss = 0.6663 (1.604 sec/step)\n",
      "INFO:tensorflow:global step 197: loss = 0.4389 (1.566 sec/step)\n",
      "INFO:tensorflow:global step 198: loss = 0.8204 (1.674 sec/step)\n",
      "INFO:tensorflow:global step 199: loss = 1.1156 (1.428 sec/step)\n",
      "INFO:tensorflow:global step 200: loss = 0.5486 (1.476 sec/step)\n",
      "INFO:tensorflow:global step 201: loss = 0.6471 (1.702 sec/step)\n",
      "INFO:tensorflow:global step 202: loss = 1.8576 (1.666 sec/step)\n",
      "INFO:tensorflow:global step 203: loss = 0.5986 (1.640 sec/step)\n",
      "INFO:tensorflow:global step 204: loss = 0.6564 (1.702 sec/step)\n",
      "INFO:tensorflow:global step 205: loss = 0.7220 (1.426 sec/step)\n",
      "INFO:tensorflow:global step 206: loss = 0.5788 (1.677 sec/step)\n",
      "INFO:tensorflow:global step 207: loss = 0.4880 (1.268 sec/step)\n",
      "INFO:tensorflow:global step 208: loss = 0.7386 (1.748 sec/step)\n",
      "INFO:tensorflow:global step 209: loss = 0.5085 (1.540 sec/step)\n",
      "INFO:tensorflow:global step 210: loss = 1.6806 (1.765 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 211: loss = 0.6837 (1.272 sec/step)\n",
      "INFO:tensorflow:global step 212: loss = 0.6585 (1.133 sec/step)\n",
      "INFO:tensorflow:global step 213: loss = 0.6838 (1.042 sec/step)\n",
      "INFO:tensorflow:global step 214: loss = 0.7713 (1.308 sec/step)\n",
      "INFO:tensorflow:global step 215: loss = 0.6834 (1.899 sec/step)\n",
      "INFO:tensorflow:global step 216: loss = 0.5352 (1.354 sec/step)\n",
      "INFO:tensorflow:global step 217: loss = 0.6188 (1.258 sec/step)\n",
      "INFO:tensorflow:global step 218: loss = 0.8342 (1.396 sec/step)\n",
      "INFO:tensorflow:global step 219: loss = 0.4663 (1.553 sec/step)\n",
      "INFO:tensorflow:global step 220: loss = 0.4578 (1.559 sec/step)\n",
      "INFO:tensorflow:global step 221: loss = 0.5273 (1.235 sec/step)\n",
      "INFO:tensorflow:global step 222: loss = 0.4964 (1.279 sec/step)\n",
      "INFO:tensorflow:global step 223: loss = 0.4721 (1.478 sec/step)\n",
      "INFO:tensorflow:global step 224: loss = 0.6984 (2.160 sec/step)\n",
      "INFO:tensorflow:global step 225: loss = 0.4805 (1.573 sec/step)\n",
      "INFO:tensorflow:global step 226: loss = 0.4912 (1.253 sec/step)\n",
      "INFO:tensorflow:global step 227: loss = 0.4464 (1.486 sec/step)\n",
      "INFO:tensorflow:global step 228: loss = 0.7229 (1.547 sec/step)\n",
      "INFO:tensorflow:global step 229: loss = 0.4607 (1.700 sec/step)\n",
      "INFO:tensorflow:global step 230: loss = 0.4767 (1.557 sec/step)\n",
      "INFO:tensorflow:global step 231: loss = 0.8011 (1.559 sec/step)\n",
      "INFO:tensorflow:global step 232: loss = 0.4312 (1.327 sec/step)\n",
      "INFO:tensorflow:global step 233: loss = 0.4457 (1.473 sec/step)\n",
      "INFO:tensorflow:global step 234: loss = 0.4984 (1.393 sec/step)\n",
      "INFO:tensorflow:global step 235: loss = 0.5376 (1.595 sec/step)\n",
      "INFO:tensorflow:global step 236: loss = 0.4641 (1.794 sec/step)\n",
      "INFO:tensorflow:global step 237: loss = 0.5238 (1.377 sec/step)\n",
      "INFO:tensorflow:global step 238: loss = 0.4688 (1.511 sec/step)\n",
      "INFO:tensorflow:global step 239: loss = 0.4388 (1.413 sec/step)\n",
      "INFO:tensorflow:global step 240: loss = 0.4381 (1.776 sec/step)\n",
      "INFO:tensorflow:global step 241: loss = 0.4279 (1.752 sec/step)\n",
      "INFO:tensorflow:global step 242: loss = 0.4637 (1.801 sec/step)\n",
      "INFO:tensorflow:global step 243: loss = 0.5425 (1.547 sec/step)\n",
      "INFO:tensorflow:global step 244: loss = 0.5011 (1.770 sec/step)\n",
      "INFO:tensorflow:global step 245: loss = 0.5762 (1.563 sec/step)\n",
      "INFO:tensorflow:global step 246: loss = 0.4163 (1.541 sec/step)\n",
      "INFO:tensorflow:global step 247: loss = 0.6376 (1.242 sec/step)\n",
      "INFO:tensorflow:global step 248: loss = 0.4136 (1.593 sec/step)\n",
      "INFO:tensorflow:global step 249: loss = 0.5842 (1.710 sec/step)\n",
      "INFO:tensorflow:global step 250: loss = 0.4253 (1.609 sec/step)\n",
      "INFO:tensorflow:global step 251: loss = 0.6474 (1.548 sec/step)\n",
      "INFO:tensorflow:global step 252: loss = 0.5153 (1.368 sec/step)\n",
      "INFO:tensorflow:global step 253: loss = 1.0805 (1.701 sec/step)\n",
      "INFO:tensorflow:global step 254: loss = 0.4831 (1.988 sec/step)\n",
      "INFO:tensorflow:global step 255: loss = 0.5022 (1.457 sec/step)\n",
      "INFO:tensorflow:global step 256: loss = 0.5734 (1.762 sec/step)\n",
      "INFO:tensorflow:global step 257: loss = 0.5665 (1.284 sec/step)\n",
      "INFO:tensorflow:global step 258: loss = 0.4892 (1.531 sec/step)\n",
      "INFO:tensorflow:global step 259: loss = 0.5156 (1.700 sec/step)\n",
      "INFO:tensorflow:global step 260: loss = 0.4693 (1.413 sec/step)\n",
      "INFO:tensorflow:global step 261: loss = 0.5240 (1.808 sec/step)\n",
      "INFO:tensorflow:global step 262: loss = 0.5329 (1.707 sec/step)\n",
      "INFO:tensorflow:global step 263: loss = 0.5163 (1.264 sec/step)\n",
      "INFO:tensorflow:global step 264: loss = 0.5644 (1.583 sec/step)\n",
      "INFO:tensorflow:global step 265: loss = 0.4597 (1.231 sec/step)\n",
      "INFO:tensorflow:global step 266: loss = 0.4575 (1.879 sec/step)\n",
      "INFO:tensorflow:global step 267: loss = 0.4594 (1.447 sec/step)\n",
      "INFO:tensorflow:global step 268: loss = 0.5734 (1.644 sec/step)\n",
      "INFO:tensorflow:global step 269: loss = 0.4614 (1.437 sec/step)\n",
      "INFO:tensorflow:global step 270: loss = 0.6457 (1.554 sec/step)\n",
      "INFO:tensorflow:global step 271: loss = 0.4733 (1.084 sec/step)\n",
      "INFO:tensorflow:global step 272: loss = 0.4543 (1.527 sec/step)\n",
      "INFO:tensorflow:global step 273: loss = 0.4446 (1.696 sec/step)\n",
      "INFO:tensorflow:global step 274: loss = 0.4531 (1.295 sec/step)\n",
      "INFO:tensorflow:global step 275: loss = 0.4269 (1.491 sec/step)\n",
      "INFO:tensorflow:global step 276: loss = 0.4072 (1.288 sec/step)\n",
      "INFO:tensorflow:global step 277: loss = 0.4239 (1.288 sec/step)\n",
      "INFO:tensorflow:global step 278: loss = 0.3926 (1.603 sec/step)\n",
      "INFO:tensorflow:global step 279: loss = 0.4184 (1.836 sec/step)\n",
      "INFO:tensorflow:global step 280: loss = 0.3934 (1.119 sec/step)\n",
      "INFO:tensorflow:global step 281: loss = 0.4012 (1.438 sec/step)\n",
      "INFO:tensorflow:global step 282: loss = 0.5855 (1.415 sec/step)\n",
      "INFO:tensorflow:global step 283: loss = 0.4185 (1.179 sec/step)\n",
      "INFO:tensorflow:global step 284: loss = 0.3944 (1.418 sec/step)\n",
      "INFO:tensorflow:global step 285: loss = 0.3872 (1.396 sec/step)\n",
      "INFO:tensorflow:global step 286: loss = 0.4141 (1.041 sec/step)\n",
      "INFO:tensorflow:global step 287: loss = 0.3983 (1.339 sec/step)\n",
      "INFO:tensorflow:global step 288: loss = 0.5536 (1.336 sec/step)\n",
      "INFO:tensorflow:global step 289: loss = 0.4243 (1.219 sec/step)\n",
      "INFO:tensorflow:global step 290: loss = 0.3900 (1.195 sec/step)\n",
      "INFO:tensorflow:global step 291: loss = 0.3856 (1.497 sec/step)\n",
      "INFO:tensorflow:global step 292: loss = 0.4587 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 293: loss = 0.6743 (1.981 sec/step)\n",
      "INFO:tensorflow:global step 294: loss = 0.3822 (1.673 sec/step)\n",
      "INFO:tensorflow:global step 295: loss = 0.4305 (1.557 sec/step)\n",
      "INFO:tensorflow:global step 296: loss = 0.4098 (1.744 sec/step)\n",
      "INFO:tensorflow:global step 297: loss = 0.3794 (1.246 sec/step)\n",
      "INFO:tensorflow:global step 298: loss = 0.3842 (1.157 sec/step)\n",
      "INFO:tensorflow:global step 299: loss = 0.4007 (1.357 sec/step)\n",
      "INFO:tensorflow:global step 300: loss = 0.5020 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 301: loss = 0.4195 (1.729 sec/step)\n",
      "INFO:tensorflow:global step 302: loss = 0.4079 (1.585 sec/step)\n",
      "INFO:tensorflow:global step 303: loss = 0.3823 (1.412 sec/step)\n",
      "INFO:tensorflow:global step 304: loss = 0.3718 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 305: loss = 0.3932 (1.537 sec/step)\n",
      "INFO:tensorflow:global step 306: loss = 0.3699 (1.499 sec/step)\n",
      "INFO:tensorflow:global step 307: loss = 0.3789 (1.537 sec/step)\n",
      "INFO:tensorflow:global step 308: loss = 0.3705 (1.637 sec/step)\n",
      "INFO:tensorflow:global step 309: loss = 0.3720 (1.354 sec/step)\n",
      "INFO:tensorflow:global step 310: loss = 0.3657 (1.194 sec/step)\n",
      "INFO:tensorflow:global step 311: loss = 0.3764 (1.182 sec/step)\n",
      "INFO:tensorflow:global step 312: loss = 0.3712 (1.114 sec/step)\n",
      "INFO:tensorflow:global step 313: loss = 0.3697 (1.359 sec/step)\n",
      "INFO:tensorflow:global step 314: loss = 0.3628 (1.712 sec/step)\n",
      "INFO:tensorflow:global step 315: loss = 0.3722 (1.703 sec/step)\n",
      "INFO:tensorflow:global step 316: loss = 0.3622 (1.407 sec/step)\n",
      "INFO:tensorflow:global step 317: loss = 0.3620 (1.386 sec/step)\n",
      "INFO:tensorflow:global step 318: loss = 0.4388 (1.254 sec/step)\n",
      "INFO:tensorflow:global step 319: loss = 0.3579 (1.391 sec/step)\n",
      "INFO:tensorflow:global step 320: loss = 0.3576 (1.277 sec/step)\n",
      "INFO:tensorflow:global step 321: loss = 0.4865 (1.734 sec/step)\n",
      "INFO:tensorflow:global step 322: loss = 0.3630 (1.225 sec/step)\n",
      "INFO:tensorflow:global step 323: loss = 0.3560 (1.457 sec/step)\n",
      "INFO:tensorflow:global step 324: loss = 0.4338 (1.441 sec/step)\n",
      "INFO:tensorflow:global step 325: loss = 0.3600 (1.639 sec/step)\n",
      "INFO:tensorflow:global step 326: loss = 0.3537 (1.257 sec/step)\n",
      "INFO:tensorflow:global step 327: loss = 0.3531 (1.657 sec/step)\n",
      "INFO:tensorflow:global step 328: loss = 0.3866 (1.277 sec/step)\n",
      "INFO:tensorflow:global step 329: loss = 0.3520 (1.042 sec/step)\n",
      "INFO:tensorflow:global step 330: loss = 0.3510 (1.141 sec/step)\n",
      "INFO:tensorflow:global step 331: loss = 0.3526 (1.328 sec/step)\n",
      "INFO:tensorflow:global step 332: loss = 0.3521 (1.165 sec/step)\n",
      "INFO:tensorflow:global step 333: loss = 0.6074 (1.333 sec/step)\n",
      "INFO:tensorflow:global step 334: loss = 0.3496 (1.301 sec/step)\n",
      "INFO:tensorflow:global step 335: loss = 0.3598 (1.163 sec/step)\n",
      "INFO:tensorflow:global step 336: loss = 0.3661 (1.213 sec/step)\n",
      "INFO:tensorflow:global step 337: loss = 0.3559 (1.096 sec/step)\n",
      "INFO:tensorflow:global step 338: loss = 0.5024 (1.245 sec/step)\n",
      "INFO:tensorflow:global step 339: loss = 0.3499 (1.345 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 340: loss = 0.4615 (1.529 sec/step)\n",
      "INFO:tensorflow:global step 341: loss = 0.4318 (1.524 sec/step)\n",
      "INFO:tensorflow:global step 342: loss = 0.3623 (1.105 sec/step)\n",
      "INFO:tensorflow:global step 343: loss = 0.4985 (0.986 sec/step)\n",
      "INFO:tensorflow:global step 344: loss = 0.3461 (1.394 sec/step)\n",
      "INFO:tensorflow:global step 345: loss = 0.4807 (1.146 sec/step)\n",
      "INFO:tensorflow:global step 346: loss = 0.3593 (1.205 sec/step)\n",
      "INFO:tensorflow:global step 347: loss = 0.3463 (1.461 sec/step)\n",
      "INFO:tensorflow:global step 348: loss = 0.4606 (0.925 sec/step)\n",
      "INFO:tensorflow:global step 349: loss = 0.5958 (1.210 sec/step)\n",
      "INFO:tensorflow:global step 350: loss = 0.3536 (1.676 sec/step)\n",
      "INFO:tensorflow:global step 351: loss = 0.3653 (1.360 sec/step)\n",
      "INFO:tensorflow:global step 352: loss = 0.3894 (1.240 sec/step)\n",
      "INFO:tensorflow:global step 353: loss = 0.4191 (1.241 sec/step)\n",
      "INFO:tensorflow:global step 354: loss = 0.4480 (1.406 sec/step)\n",
      "INFO:tensorflow:global step 355: loss = 0.3684 (1.122 sec/step)\n",
      "INFO:tensorflow:global step 356: loss = 0.4859 (1.295 sec/step)\n",
      "INFO:tensorflow:global step 357: loss = 0.4424 (1.434 sec/step)\n",
      "INFO:tensorflow:global step 358: loss = 0.3569 (1.208 sec/step)\n",
      "INFO:tensorflow:global step 359: loss = 0.3872 (1.435 sec/step)\n",
      "INFO:tensorflow:Saving checkpoint to path /tmp/inception_finetuned1/model.ckpt\n",
      "INFO:tensorflow:global step 360: loss = 0.4032 (1.724 sec/step)\n",
      "INFO:tensorflow:global_step/sec: 0.601767\n",
      "INFO:tensorflow:Recording summary at step 360.\n",
      "INFO:tensorflow:global step 361: loss = 0.3631 (2.795 sec/step)\n",
      "INFO:tensorflow:global step 362: loss = 0.4983 (1.160 sec/step)\n",
      "INFO:tensorflow:global step 363: loss = 0.4230 (1.176 sec/step)\n",
      "INFO:tensorflow:global step 364: loss = 0.3504 (1.201 sec/step)\n",
      "INFO:tensorflow:global step 365: loss = 0.3444 (1.956 sec/step)\n",
      "INFO:tensorflow:global step 366: loss = 0.4033 (1.148 sec/step)\n",
      "INFO:tensorflow:global step 367: loss = 0.3368 (1.224 sec/step)\n",
      "INFO:tensorflow:global step 368: loss = 0.3352 (1.230 sec/step)\n",
      "INFO:tensorflow:global step 369: loss = 0.3611 (1.238 sec/step)\n",
      "INFO:tensorflow:global step 370: loss = 0.3690 (1.686 sec/step)\n",
      "INFO:tensorflow:global step 371: loss = 0.3318 (1.547 sec/step)\n",
      "INFO:tensorflow:global step 372: loss = 0.3433 (1.459 sec/step)\n",
      "INFO:tensorflow:global step 373: loss = 0.3706 (1.202 sec/step)\n",
      "INFO:tensorflow:global step 374: loss = 0.3238 (1.313 sec/step)\n",
      "INFO:tensorflow:global step 375: loss = 0.4345 (1.282 sec/step)\n",
      "INFO:tensorflow:global step 376: loss = 0.3475 (1.295 sec/step)\n",
      "INFO:tensorflow:global step 377: loss = 0.4751 (1.783 sec/step)\n",
      "INFO:tensorflow:global step 378: loss = 0.5151 (1.031 sec/step)\n",
      "INFO:tensorflow:global step 379: loss = 0.3299 (1.327 sec/step)\n",
      "INFO:tensorflow:global step 380: loss = 0.4378 (0.950 sec/step)\n",
      "INFO:tensorflow:global step 381: loss = 0.3687 (1.507 sec/step)\n",
      "INFO:tensorflow:global step 382: loss = 0.4136 (1.439 sec/step)\n",
      "INFO:tensorflow:global step 383: loss = 0.3436 (1.348 sec/step)\n",
      "INFO:tensorflow:global step 384: loss = 0.3267 (0.997 sec/step)\n",
      "INFO:tensorflow:global step 385: loss = 0.3204 (0.942 sec/step)\n",
      "INFO:tensorflow:global step 386: loss = 0.3209 (1.239 sec/step)\n",
      "INFO:tensorflow:global step 387: loss = 0.3308 (1.345 sec/step)\n",
      "INFO:tensorflow:global step 388: loss = 0.3141 (1.127 sec/step)\n",
      "INFO:tensorflow:global step 389: loss = 0.3536 (1.046 sec/step)\n",
      "INFO:tensorflow:global step 390: loss = 0.3120 (0.964 sec/step)\n",
      "INFO:tensorflow:global step 391: loss = 0.3375 (1.321 sec/step)\n",
      "INFO:tensorflow:global step 392: loss = 0.3161 (1.352 sec/step)\n",
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      "INFO:tensorflow:global step 394: loss = 0.3111 (1.253 sec/step)\n",
      "INFO:tensorflow:global step 395: loss = 0.3193 (1.130 sec/step)\n",
      "INFO:tensorflow:global step 396: loss = 0.4212 (1.035 sec/step)\n",
      "INFO:tensorflow:global step 397: loss = 0.3095 (1.310 sec/step)\n",
      "INFO:tensorflow:global step 398: loss = 0.3085 (1.285 sec/step)\n",
      "INFO:tensorflow:global step 399: loss = 0.3065 (1.200 sec/step)\n",
      "INFO:tensorflow:global step 400: loss = 0.6558 (1.102 sec/step)\n",
      "INFO:tensorflow:global step 401: loss = 0.3143 (1.088 sec/step)\n",
      "INFO:tensorflow:global step 402: loss = 0.3043 (1.202 sec/step)\n",
      "INFO:tensorflow:global step 403: loss = 0.3040 (1.102 sec/step)\n",
      "INFO:tensorflow:global step 404: loss = 1.1517 (1.188 sec/step)\n",
      "INFO:tensorflow:global step 405: loss = 0.3133 (1.173 sec/step)\n",
      "INFO:tensorflow:global step 406: loss = 0.3452 (1.129 sec/step)\n",
      "INFO:tensorflow:global step 407: loss = 0.3250 (1.183 sec/step)\n",
      "INFO:tensorflow:global step 408: loss = 0.3948 (1.290 sec/step)\n",
      "INFO:tensorflow:global step 409: loss = 0.3168 (1.107 sec/step)\n",
      "INFO:tensorflow:global step 410: loss = 0.3400 (1.028 sec/step)\n",
      "INFO:tensorflow:global step 411: loss = 0.3083 (1.403 sec/step)\n",
      "INFO:tensorflow:global step 412: loss = 0.4004 (1.192 sec/step)\n",
      "INFO:tensorflow:global step 413: loss = 0.3070 (1.437 sec/step)\n",
      "INFO:tensorflow:global step 414: loss = 0.3541 (1.197 sec/step)\n",
      "INFO:tensorflow:global step 415: loss = 0.3344 (1.186 sec/step)\n",
      "INFO:tensorflow:global step 416: loss = 0.3504 (1.208 sec/step)\n",
      "INFO:tensorflow:global step 417: loss = 0.3425 (1.248 sec/step)\n",
      "INFO:tensorflow:global step 418: loss = 0.3180 (1.352 sec/step)\n",
      "INFO:tensorflow:global step 419: loss = 0.3086 (1.129 sec/step)\n",
      "INFO:tensorflow:global step 420: loss = 0.3106 (1.492 sec/step)\n",
      "INFO:tensorflow:global step 421: loss = 0.3064 (1.141 sec/step)\n",
      "INFO:tensorflow:global step 422: loss = 0.3100 (1.407 sec/step)\n",
      "INFO:tensorflow:global step 423: loss = 0.3135 (1.107 sec/step)\n",
      "INFO:tensorflow:global step 424: loss = 0.3285 (1.473 sec/step)\n",
      "INFO:tensorflow:global step 425: loss = 0.3019 (1.552 sec/step)\n",
      "INFO:tensorflow:global step 426: loss = 0.3013 (1.586 sec/step)\n",
      "INFO:tensorflow:global step 427: loss = 0.3420 (1.072 sec/step)\n",
      "INFO:tensorflow:global step 428: loss = 0.3035 (1.168 sec/step)\n",
      "INFO:tensorflow:global step 429: loss = 0.2991 (1.180 sec/step)\n",
      "INFO:tensorflow:global step 430: loss = 0.3081 (1.345 sec/step)\n",
      "INFO:tensorflow:global step 431: loss = 0.2960 (1.552 sec/step)\n",
      "INFO:tensorflow:global step 432: loss = 0.2959 (1.351 sec/step)\n",
      "INFO:tensorflow:global step 433: loss = 0.3983 (1.478 sec/step)\n",
      "INFO:tensorflow:global step 434: loss = 0.2964 (1.505 sec/step)\n",
      "INFO:tensorflow:global step 435: loss = 0.3546 (1.580 sec/step)\n",
      "INFO:tensorflow:global step 436: loss = 0.2950 (1.353 sec/step)\n",
      "INFO:tensorflow:global step 437: loss = 0.6157 (1.991 sec/step)\n",
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      "INFO:tensorflow:global step 439: loss = 0.5346 (1.430 sec/step)\n",
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      "INFO:tensorflow:global step 441: loss = 0.3673 (1.490 sec/step)\n",
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      "INFO:tensorflow:global step 443: loss = 0.3728 (1.611 sec/step)\n",
      "INFO:tensorflow:global step 444: loss = 0.3121 (1.297 sec/step)\n",
      "INFO:tensorflow:global step 445: loss = 0.3855 (1.011 sec/step)\n",
      "INFO:tensorflow:global step 446: loss = 0.3612 (1.506 sec/step)\n",
      "INFO:tensorflow:global step 447: loss = 0.4369 (1.245 sec/step)\n",
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      "INFO:tensorflow:global step 449: loss = 0.6028 (1.124 sec/step)\n",
      "INFO:tensorflow:global step 450: loss = 0.4105 (1.330 sec/step)\n",
      "INFO:tensorflow:global step 451: loss = 0.4491 (1.221 sec/step)\n",
      "INFO:tensorflow:global step 452: loss = 0.4078 (1.373 sec/step)\n",
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      "INFO:tensorflow:global step 455: loss = 0.3951 (1.138 sec/step)\n",
      "INFO:tensorflow:global step 456: loss = 0.3975 (1.467 sec/step)\n",
      "INFO:tensorflow:global step 457: loss = 0.3746 (1.398 sec/step)\n",
      "INFO:tensorflow:global step 458: loss = 0.3340 (1.011 sec/step)\n",
      "INFO:tensorflow:global step 459: loss = 0.4830 (1.531 sec/step)\n",
      "INFO:tensorflow:global step 460: loss = 0.3176 (1.641 sec/step)\n",
      "INFO:tensorflow:global step 461: loss = 0.2975 (1.464 sec/step)\n",
      "INFO:tensorflow:global step 462: loss = 0.3322 (1.285 sec/step)\n",
      "INFO:tensorflow:global step 463: loss = 0.3102 (1.942 sec/step)\n",
      "INFO:tensorflow:global step 464: loss = 0.4537 (1.608 sec/step)\n",
      "INFO:tensorflow:global step 465: loss = 0.3517 (1.603 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 466: loss = 0.2965 (1.651 sec/step)\n",
      "INFO:tensorflow:global step 467: loss = 0.2888 (1.828 sec/step)\n",
      "INFO:tensorflow:global step 468: loss = 0.3187 (1.502 sec/step)\n",
      "INFO:tensorflow:global step 469: loss = 0.2882 (1.776 sec/step)\n",
      "INFO:tensorflow:global step 470: loss = 0.2855 (1.842 sec/step)\n",
      "INFO:tensorflow:global step 471: loss = 0.3733 (1.531 sec/step)\n",
      "INFO:tensorflow:global step 472: loss = 0.3981 (1.588 sec/step)\n",
      "INFO:tensorflow:global step 473: loss = 0.3791 (1.533 sec/step)\n",
      "INFO:tensorflow:global step 474: loss = 0.2803 (1.134 sec/step)\n",
      "INFO:tensorflow:global step 475: loss = 0.2847 (1.546 sec/step)\n",
      "INFO:tensorflow:global step 476: loss = 0.2756 (1.782 sec/step)\n",
      "INFO:tensorflow:global step 477: loss = 0.2782 (1.641 sec/step)\n",
      "INFO:tensorflow:global step 478: loss = 0.2761 (1.334 sec/step)\n",
      "INFO:tensorflow:global step 479: loss = 0.3066 (1.824 sec/step)\n",
      "INFO:tensorflow:global step 480: loss = 0.2875 (1.596 sec/step)\n",
      "INFO:tensorflow:global step 481: loss = 0.4737 (1.933 sec/step)\n",
      "INFO:tensorflow:global step 482: loss = 0.2851 (1.775 sec/step)\n",
      "INFO:tensorflow:global step 483: loss = 0.4075 (1.355 sec/step)\n",
      "INFO:tensorflow:global step 484: loss = 0.3266 (1.570 sec/step)\n",
      "INFO:tensorflow:global step 485: loss = 0.2863 (1.445 sec/step)\n",
      "INFO:tensorflow:global step 486: loss = 0.4511 (1.669 sec/step)\n",
      "INFO:tensorflow:global step 487: loss = 0.2975 (1.658 sec/step)\n",
      "INFO:tensorflow:global step 488: loss = 0.4443 (1.532 sec/step)\n",
      "INFO:tensorflow:global step 489: loss = 0.3204 (1.583 sec/step)\n",
      "INFO:tensorflow:global step 490: loss = 0.3600 (1.505 sec/step)\n",
      "INFO:tensorflow:global step 491: loss = 0.2826 (1.584 sec/step)\n",
      "INFO:tensorflow:global step 492: loss = 0.3432 (1.475 sec/step)\n",
      "INFO:tensorflow:global step 493: loss = 0.9962 (1.434 sec/step)\n",
      "INFO:tensorflow:global step 494: loss = 0.2796 (1.387 sec/step)\n",
      "INFO:tensorflow:global step 495: loss = 0.2805 (1.865 sec/step)\n",
      "INFO:tensorflow:global step 496: loss = 0.3005 (1.225 sec/step)\n",
      "INFO:tensorflow:global step 497: loss = 0.3637 (1.527 sec/step)\n",
      "INFO:tensorflow:global step 498: loss = 0.5227 (1.982 sec/step)\n",
      "INFO:tensorflow:global step 499: loss = 1.0069 (1.548 sec/step)\n",
      "INFO:tensorflow:global step 500: loss = 0.3195 (1.536 sec/step)\n",
      "INFO:tensorflow:global step 501: loss = 0.7658 (1.744 sec/step)\n",
      "INFO:tensorflow:global step 502: loss = 0.7464 (1.204 sec/step)\n",
      "INFO:tensorflow:global step 503: loss = 0.3840 (1.405 sec/step)\n",
      "INFO:tensorflow:global step 504: loss = 0.3714 (1.490 sec/step)\n",
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      "INFO:tensorflow:global step 506: loss = 0.3709 (1.685 sec/step)\n",
      "INFO:tensorflow:global step 507: loss = 0.3558 (1.798 sec/step)\n",
      "INFO:tensorflow:global step 508: loss = 0.4133 (1.908 sec/step)\n",
      "INFO:tensorflow:global step 509: loss = 0.4097 (1.291 sec/step)\n",
      "INFO:tensorflow:global step 510: loss = 0.3775 (1.860 sec/step)\n",
      "INFO:tensorflow:global step 511: loss = 0.3042 (1.886 sec/step)\n",
      "INFO:tensorflow:global step 512: loss = 0.4150 (1.808 sec/step)\n",
      "INFO:tensorflow:global step 513: loss = 0.3959 (1.426 sec/step)\n",
      "INFO:tensorflow:global step 514: loss = 0.3582 (1.776 sec/step)\n",
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      "INFO:tensorflow:global step 519: loss = 0.3086 (1.813 sec/step)\n",
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      "INFO:tensorflow:global step 521: loss = 0.3028 (1.934 sec/step)\n",
      "INFO:tensorflow:global step 522: loss = 0.3037 (1.491 sec/step)\n",
      "INFO:tensorflow:global step 523: loss = 0.2959 (1.826 sec/step)\n",
      "INFO:tensorflow:global step 524: loss = 0.7041 (1.584 sec/step)\n",
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      "INFO:tensorflow:global step 526: loss = 0.3482 (1.727 sec/step)\n",
      "INFO:tensorflow:global step 527: loss = 0.2991 (1.544 sec/step)\n",
      "INFO:tensorflow:global step 528: loss = 0.3392 (1.724 sec/step)\n",
      "INFO:tensorflow:global step 529: loss = 0.4465 (1.284 sec/step)\n",
      "INFO:tensorflow:global step 530: loss = 0.3336 (1.450 sec/step)\n",
      "INFO:tensorflow:global step 531: loss = 0.3134 (2.150 sec/step)\n",
      "INFO:tensorflow:global step 532: loss = 0.3788 (1.034 sec/step)\n",
      "INFO:tensorflow:global step 533: loss = 0.3664 (1.891 sec/step)\n",
      "INFO:tensorflow:global step 534: loss = 0.3490 (1.443 sec/step)\n",
      "INFO:tensorflow:global step 535: loss = 0.3054 (1.442 sec/step)\n",
      "INFO:tensorflow:global step 536: loss = 0.2951 (1.655 sec/step)\n",
      "INFO:tensorflow:global step 537: loss = 0.3347 (1.596 sec/step)\n",
      "INFO:tensorflow:global step 538: loss = 0.4463 (1.331 sec/step)\n",
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      "INFO:tensorflow:global step 540: loss = 0.3027 (1.898 sec/step)\n",
      "INFO:tensorflow:global step 541: loss = 0.3100 (1.481 sec/step)\n",
      "INFO:tensorflow:global step 542: loss = 0.3224 (1.223 sec/step)\n",
      "INFO:tensorflow:global step 543: loss = 0.2839 (1.728 sec/step)\n",
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      "INFO:tensorflow:global step 545: loss = 0.2947 (1.684 sec/step)\n",
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      "INFO:tensorflow:global step 548: loss = 0.2797 (1.324 sec/step)\n",
      "INFO:tensorflow:global step 549: loss = 0.2827 (1.547 sec/step)\n",
      "INFO:tensorflow:global step 550: loss = 0.2792 (1.870 sec/step)\n",
      "INFO:tensorflow:global step 551: loss = 0.2824 (1.747 sec/step)\n",
      "INFO:tensorflow:global step 552: loss = 0.3088 (1.509 sec/step)\n",
      "INFO:tensorflow:global step 553: loss = 0.2825 (1.845 sec/step)\n",
      "INFO:tensorflow:global step 554: loss = 0.2862 (1.478 sec/step)\n",
      "INFO:tensorflow:global step 555: loss = 0.3487 (1.280 sec/step)\n",
      "INFO:tensorflow:global step 556: loss = 0.2787 (2.114 sec/step)\n",
      "INFO:tensorflow:global step 557: loss = 0.5436 (1.578 sec/step)\n",
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      "INFO:tensorflow:global step 563: loss = 0.2735 (1.638 sec/step)\n",
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      "INFO:tensorflow:global step 567: loss = 0.2869 (1.695 sec/step)\n",
      "INFO:tensorflow:global step 568: loss = 0.2925 (1.493 sec/step)\n",
      "INFO:tensorflow:global step 569: loss = 0.2901 (1.370 sec/step)\n",
      "INFO:tensorflow:global step 570: loss = 0.2768 (1.267 sec/step)\n",
      "INFO:tensorflow:global step 571: loss = 0.5544 (1.418 sec/step)\n",
      "INFO:tensorflow:global step 572: loss = 0.3011 (1.864 sec/step)\n",
      "INFO:tensorflow:global step 573: loss = 0.3336 (1.937 sec/step)\n",
      "INFO:tensorflow:global step 574: loss = 0.3064 (1.412 sec/step)\n",
      "INFO:tensorflow:global step 575: loss = 0.3052 (1.403 sec/step)\n",
      "INFO:tensorflow:global step 576: loss = 0.5300 (1.316 sec/step)\n",
      "INFO:tensorflow:global step 577: loss = 0.5928 (1.547 sec/step)\n",
      "INFO:tensorflow:global step 578: loss = 0.3495 (1.501 sec/step)\n",
      "INFO:tensorflow:global step 579: loss = 0.4160 (1.738 sec/step)\n",
      "INFO:tensorflow:global step 580: loss = 0.4007 (1.766 sec/step)\n",
      "INFO:tensorflow:global step 581: loss = 0.3773 (1.611 sec/step)\n",
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      "INFO:tensorflow:global step 584: loss = 0.4301 (1.766 sec/step)\n",
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      "INFO:tensorflow:global step 588: loss = 0.4264 (1.507 sec/step)\n",
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      "INFO:tensorflow:global step 590: loss = 0.4816 (1.376 sec/step)\n",
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      "INFO:tensorflow:global step 592: loss = 0.3605 (1.771 sec/step)\n",
      "INFO:tensorflow:global step 593: loss = 0.3658 (1.045 sec/step)\n",
      "INFO:tensorflow:global step 594: loss = 0.3538 (1.471 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 595: loss = 0.3721 (1.930 sec/step)\n",
      "INFO:tensorflow:global step 596: loss = 0.3948 (1.851 sec/step)\n",
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      "INFO:tensorflow:global step 666: loss = 0.2575 (1.617 sec/step)\n",
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      "INFO:tensorflow:global step 700: loss = 0.3029 (1.332 sec/step)\n",
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      "INFO:tensorflow:global step 723: loss = 0.2424 (1.154 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 724: loss = 0.2827 (1.491 sec/step)\n",
      "INFO:tensorflow:global step 725: loss = 0.2321 (1.805 sec/step)\n",
      "INFO:tensorflow:global step 726: loss = 0.2348 (1.279 sec/step)\n",
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      "INFO:tensorflow:global step 728: loss = 0.2986 (1.726 sec/step)\n",
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      "INFO:tensorflow:global step 730: loss = 0.2454 (1.364 sec/step)\n",
      "INFO:tensorflow:global step 731: loss = 0.2211 (1.508 sec/step)\n",
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      "INFO:tensorflow:global step 733: loss = 0.2450 (1.672 sec/step)\n",
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      "INFO:tensorflow:global step 735: loss = 0.2682 (1.589 sec/step)\n",
      "INFO:tensorflow:global step 736: loss = 0.2220 (1.283 sec/step)\n",
      "INFO:tensorflow:global step 737: loss = 0.2167 (1.838 sec/step)\n",
      "INFO:tensorflow:global step 738: loss = 0.2409 (1.511 sec/step)\n",
      "INFO:tensorflow:global step 739: loss = 0.2216 (1.535 sec/step)\n",
      "INFO:tensorflow:global step 740: loss = 0.2194 (1.725 sec/step)\n",
      "INFO:tensorflow:global step 741: loss = 0.2157 (1.661 sec/step)\n",
      "INFO:tensorflow:global step 742: loss = 1.0620 (1.275 sec/step)\n",
      "INFO:tensorflow:global step 743: loss = 0.4579 (1.278 sec/step)\n",
      "INFO:tensorflow:global step 744: loss = 0.2449 (1.775 sec/step)\n",
      "INFO:tensorflow:global step 745: loss = 0.3157 (1.526 sec/step)\n",
      "INFO:tensorflow:global step 746: loss = 0.2407 (1.928 sec/step)\n",
      "INFO:tensorflow:global step 747: loss = 0.2571 (1.265 sec/step)\n",
      "INFO:tensorflow:global step 748: loss = 0.2312 (1.371 sec/step)\n",
      "INFO:tensorflow:global step 749: loss = 0.2356 (1.677 sec/step)\n",
      "INFO:tensorflow:global step 750: loss = 0.2296 (1.468 sec/step)\n",
      "INFO:tensorflow:global step 751: loss = 0.2427 (1.550 sec/step)\n",
      "INFO:tensorflow:global step 752: loss = 0.2839 (1.587 sec/step)\n",
      "INFO:tensorflow:global step 753: loss = 0.5119 (1.818 sec/step)\n",
      "INFO:tensorflow:global step 754: loss = 0.2521 (1.306 sec/step)\n",
      "INFO:tensorflow:global step 755: loss = 0.3701 (1.286 sec/step)\n",
      "INFO:tensorflow:global step 756: loss = 0.3044 (1.886 sec/step)\n",
      "INFO:tensorflow:Saving checkpoint to path /tmp/inception_finetuned1/model.ckpt\n",
      "INFO:tensorflow:global_step/sec: 0.660048\n",
      "INFO:tensorflow:global step 757: loss = 0.2234 (1.650 sec/step)\n",
      "INFO:tensorflow:Recording summary at step 757.\n",
      "INFO:tensorflow:global step 758: loss = 0.2430 (3.131 sec/step)\n",
      "INFO:tensorflow:global step 759: loss = 0.2758 (1.481 sec/step)\n",
      "INFO:tensorflow:global step 760: loss = 0.2328 (1.532 sec/step)\n",
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      "INFO:tensorflow:global step 762: loss = 0.2171 (2.047 sec/step)\n",
      "INFO:tensorflow:global step 763: loss = 0.2166 (1.472 sec/step)\n",
      "INFO:tensorflow:global step 764: loss = 0.2142 (1.596 sec/step)\n",
      "INFO:tensorflow:global step 765: loss = 0.2362 (1.243 sec/step)\n",
      "INFO:tensorflow:global step 766: loss = 0.2132 (1.917 sec/step)\n",
      "INFO:tensorflow:global step 767: loss = 0.2296 (1.317 sec/step)\n",
      "INFO:tensorflow:global step 768: loss = 0.2214 (1.675 sec/step)\n",
      "INFO:tensorflow:global step 769: loss = 0.2559 (1.511 sec/step)\n",
      "INFO:tensorflow:global step 770: loss = 0.3377 (1.274 sec/step)\n",
      "INFO:tensorflow:global step 771: loss = 0.2080 (1.721 sec/step)\n",
      "INFO:tensorflow:global step 772: loss = 0.2085 (1.545 sec/step)\n",
      "INFO:tensorflow:global step 773: loss = 0.2099 (1.491 sec/step)\n",
      "INFO:tensorflow:global step 774: loss = 0.2071 (1.485 sec/step)\n",
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      "INFO:tensorflow:global step 777: loss = 0.2057 (1.517 sec/step)\n",
      "INFO:tensorflow:global step 778: loss = 0.2324 (1.665 sec/step)\n",
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      "INFO:tensorflow:global step 780: loss = 0.2059 (1.492 sec/step)\n",
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      "INFO:tensorflow:global step 787: loss = 0.2277 (1.511 sec/step)\n",
      "INFO:tensorflow:global step 788: loss = 0.2153 (1.548 sec/step)\n",
      "INFO:tensorflow:global step 789: loss = 0.2107 (1.523 sec/step)\n",
      "INFO:tensorflow:global step 790: loss = 0.2437 (1.407 sec/step)\n",
      "INFO:tensorflow:global step 791: loss = 0.2101 (1.455 sec/step)\n",
      "INFO:tensorflow:global step 792: loss = 0.2378 (1.792 sec/step)\n",
      "INFO:tensorflow:global step 793: loss = 0.2714 (1.320 sec/step)\n",
      "INFO:tensorflow:global step 794: loss = 0.2237 (2.140 sec/step)\n",
      "INFO:tensorflow:global step 795: loss = 0.2242 (1.389 sec/step)\n",
      "INFO:tensorflow:global step 796: loss = 0.2137 (1.663 sec/step)\n",
      "INFO:tensorflow:global step 797: loss = 0.2142 (1.687 sec/step)\n",
      "INFO:tensorflow:global step 798: loss = 0.2125 (1.593 sec/step)\n",
      "INFO:tensorflow:global step 799: loss = 0.2146 (1.280 sec/step)\n",
      "INFO:tensorflow:global step 800: loss = 0.2192 (1.272 sec/step)\n",
      "INFO:tensorflow:global step 801: loss = 0.2139 (1.397 sec/step)\n",
      "INFO:tensorflow:global step 802: loss = 0.2117 (1.562 sec/step)\n",
      "INFO:tensorflow:global step 803: loss = 0.2121 (1.679 sec/step)\n",
      "INFO:tensorflow:global step 804: loss = 0.2112 (1.152 sec/step)\n",
      "INFO:tensorflow:global step 805: loss = 0.2123 (1.461 sec/step)\n",
      "INFO:tensorflow:global step 806: loss = 0.2140 (1.819 sec/step)\n",
      "INFO:tensorflow:global step 807: loss = 0.3205 (1.469 sec/step)\n",
      "INFO:tensorflow:global step 808: loss = 0.2096 (1.499 sec/step)\n",
      "INFO:tensorflow:global step 809: loss = 0.2171 (1.369 sec/step)\n",
      "INFO:tensorflow:global step 810: loss = 0.2118 (1.714 sec/step)\n",
      "INFO:tensorflow:global step 811: loss = 0.2099 (2.016 sec/step)\n",
      "INFO:tensorflow:global step 812: loss = 0.2141 (1.264 sec/step)\n",
      "INFO:tensorflow:global step 813: loss = 0.2169 (1.684 sec/step)\n",
      "INFO:tensorflow:global step 814: loss = 0.2065 (1.379 sec/step)\n",
      "INFO:tensorflow:global step 815: loss = 0.2061 (1.405 sec/step)\n",
      "INFO:tensorflow:global step 816: loss = 0.2061 (1.639 sec/step)\n",
      "INFO:tensorflow:global step 817: loss = 0.2897 (1.742 sec/step)\n",
      "INFO:tensorflow:global step 818: loss = 0.3200 (1.512 sec/step)\n",
      "INFO:tensorflow:global step 819: loss = 0.2038 (1.759 sec/step)\n",
      "INFO:tensorflow:global step 820: loss = 0.2033 (1.601 sec/step)\n",
      "INFO:tensorflow:global step 821: loss = 0.2165 (1.423 sec/step)\n",
      "INFO:tensorflow:global step 822: loss = 0.2027 (1.525 sec/step)\n",
      "INFO:tensorflow:global step 823: loss = 0.2492 (1.884 sec/step)\n",
      "INFO:tensorflow:global step 824: loss = 0.2908 (1.495 sec/step)\n",
      "INFO:tensorflow:global step 825: loss = 0.2206 (1.419 sec/step)\n",
      "INFO:tensorflow:global step 826: loss = 0.2086 (1.741 sec/step)\n",
      "INFO:tensorflow:global step 827: loss = 0.2063 (1.756 sec/step)\n",
      "INFO:tensorflow:global step 828: loss = 0.4957 (1.630 sec/step)\n",
      "INFO:tensorflow:global step 829: loss = 0.1996 (1.379 sec/step)\n",
      "INFO:tensorflow:global step 830: loss = 0.2077 (1.723 sec/step)\n",
      "INFO:tensorflow:global step 831: loss = 0.2036 (1.431 sec/step)\n",
      "INFO:tensorflow:global step 832: loss = 0.2044 (1.553 sec/step)\n",
      "INFO:tensorflow:global step 833: loss = 0.2009 (1.234 sec/step)\n",
      "INFO:tensorflow:global step 834: loss = 0.2121 (1.785 sec/step)\n",
      "INFO:tensorflow:global step 835: loss = 0.4452 (1.363 sec/step)\n",
      "INFO:tensorflow:global step 836: loss = 0.2049 (1.838 sec/step)\n",
      "INFO:tensorflow:global step 837: loss = 0.2066 (1.672 sec/step)\n",
      "INFO:tensorflow:global step 838: loss = 0.2055 (1.540 sec/step)\n",
      "INFO:tensorflow:global step 839: loss = 0.2119 (1.157 sec/step)\n",
      "INFO:tensorflow:global step 840: loss = 0.2014 (1.774 sec/step)\n",
      "INFO:tensorflow:global step 841: loss = 0.1981 (1.563 sec/step)\n",
      "INFO:tensorflow:global step 842: loss = 0.2225 (1.686 sec/step)\n",
      "INFO:tensorflow:global step 843: loss = 0.2740 (1.896 sec/step)\n",
      "INFO:tensorflow:global step 844: loss = 0.1978 (1.472 sec/step)\n",
      "INFO:tensorflow:global step 845: loss = 0.2121 (1.527 sec/step)\n",
      "INFO:tensorflow:global step 846: loss = 0.1951 (1.532 sec/step)\n",
      "INFO:tensorflow:global step 847: loss = 0.4066 (1.648 sec/step)\n",
      "INFO:tensorflow:global step 848: loss = 0.1953 (1.466 sec/step)\n",
      "INFO:tensorflow:global step 849: loss = 0.1942 (1.747 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 850: loss = 0.2415 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 851: loss = 0.2113 (1.516 sec/step)\n",
      "INFO:tensorflow:global step 852: loss = 0.1947 (1.735 sec/step)\n",
      "INFO:tensorflow:global step 853: loss = 0.1928 (1.802 sec/step)\n",
      "INFO:tensorflow:global step 854: loss = 0.1977 (1.500 sec/step)\n",
      "INFO:tensorflow:global step 855: loss = 0.1925 (1.724 sec/step)\n",
      "INFO:tensorflow:global step 856: loss = 0.1941 (1.430 sec/step)\n",
      "INFO:tensorflow:global step 857: loss = 0.1905 (1.789 sec/step)\n",
      "INFO:tensorflow:global step 858: loss = 0.1932 (1.618 sec/step)\n",
      "INFO:tensorflow:global step 859: loss = 0.1896 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 860: loss = 0.1883 (1.435 sec/step)\n",
      "INFO:tensorflow:global step 861: loss = 0.3715 (1.621 sec/step)\n",
      "INFO:tensorflow:global step 862: loss = 0.2605 (1.608 sec/step)\n",
      "INFO:tensorflow:global step 863: loss = 0.1894 (2.070 sec/step)\n",
      "INFO:tensorflow:global step 864: loss = 0.3260 (1.110 sec/step)\n",
      "INFO:tensorflow:global step 865: loss = 0.1877 (1.334 sec/step)\n",
      "INFO:tensorflow:global step 866: loss = 0.2002 (1.326 sec/step)\n",
      "INFO:tensorflow:global step 867: loss = 0.1902 (1.723 sec/step)\n",
      "INFO:tensorflow:global step 868: loss = 0.1930 (1.902 sec/step)\n",
      "INFO:tensorflow:global step 869: loss = 0.1957 (1.595 sec/step)\n",
      "INFO:tensorflow:global step 870: loss = 0.1876 (1.460 sec/step)\n",
      "INFO:tensorflow:global step 871: loss = 0.1925 (1.260 sec/step)\n",
      "INFO:tensorflow:global step 872: loss = 0.1941 (1.747 sec/step)\n",
      "INFO:tensorflow:global step 873: loss = 0.2725 (1.751 sec/step)\n",
      "INFO:tensorflow:global step 874: loss = 0.2140 (1.374 sec/step)\n",
      "INFO:tensorflow:global step 875: loss = 0.2471 (1.562 sec/step)\n",
      "INFO:tensorflow:global step 876: loss = 0.1852 (1.708 sec/step)\n",
      "INFO:tensorflow:global step 877: loss = 0.1928 (1.070 sec/step)\n",
      "INFO:tensorflow:global step 878: loss = 0.1823 (1.921 sec/step)\n",
      "INFO:tensorflow:global step 879: loss = 0.1823 (1.395 sec/step)\n",
      "INFO:tensorflow:global step 880: loss = 0.2471 (1.556 sec/step)\n",
      "INFO:tensorflow:global step 881: loss = 0.1850 (1.702 sec/step)\n",
      "INFO:tensorflow:global step 882: loss = 0.1875 (1.710 sec/step)\n",
      "INFO:tensorflow:global step 883: loss = 0.1850 (1.416 sec/step)\n",
      "INFO:tensorflow:global step 884: loss = 0.1868 (1.592 sec/step)\n",
      "INFO:tensorflow:global step 885: loss = 0.1779 (1.450 sec/step)\n",
      "INFO:tensorflow:global step 886: loss = 0.1851 (1.408 sec/step)\n",
      "INFO:tensorflow:global step 887: loss = 0.1793 (1.637 sec/step)\n",
      "INFO:tensorflow:global step 888: loss = 0.1774 (1.578 sec/step)\n",
      "INFO:tensorflow:global step 889: loss = 0.1807 (1.257 sec/step)\n",
      "INFO:tensorflow:global step 890: loss = 0.1760 (1.373 sec/step)\n",
      "INFO:tensorflow:global step 891: loss = 0.1760 (1.500 sec/step)\n",
      "INFO:tensorflow:global step 892: loss = 0.1754 (1.522 sec/step)\n",
      "INFO:tensorflow:global step 893: loss = 0.1786 (1.319 sec/step)\n",
      "INFO:tensorflow:global step 894: loss = 0.1731 (1.452 sec/step)\n",
      "INFO:tensorflow:global step 895: loss = 0.1794 (1.971 sec/step)\n",
      "INFO:tensorflow:global step 896: loss = 0.1719 (1.338 sec/step)\n",
      "INFO:tensorflow:global step 897: loss = 0.1713 (1.562 sec/step)\n",
      "INFO:tensorflow:global step 898: loss = 0.1732 (1.616 sec/step)\n",
      "INFO:tensorflow:global step 899: loss = 0.1707 (1.519 sec/step)\n",
      "INFO:tensorflow:global step 900: loss = 0.1701 (1.516 sec/step)\n",
      "INFO:tensorflow:global step 901: loss = 0.1702 (1.760 sec/step)\n",
      "INFO:tensorflow:global step 902: loss = 0.1713 (1.628 sec/step)\n",
      "INFO:tensorflow:global step 903: loss = 0.1683 (1.234 sec/step)\n",
      "INFO:tensorflow:global step 904: loss = 0.2690 (1.399 sec/step)\n",
      "INFO:tensorflow:global step 905: loss = 0.1681 (1.524 sec/step)\n",
      "INFO:tensorflow:global step 906: loss = 0.1670 (1.532 sec/step)\n",
      "INFO:tensorflow:global step 907: loss = 0.1669 (1.634 sec/step)\n",
      "INFO:tensorflow:global step 908: loss = 0.1671 (1.603 sec/step)\n",
      "INFO:tensorflow:global step 909: loss = 0.2753 (1.406 sec/step)\n",
      "INFO:tensorflow:global step 910: loss = 0.1656 (1.118 sec/step)\n",
      "INFO:tensorflow:global step 911: loss = 0.1654 (1.564 sec/step)\n",
      "INFO:tensorflow:global step 912: loss = 0.1706 (1.729 sec/step)\n",
      "INFO:tensorflow:global step 913: loss = 0.1662 (1.402 sec/step)\n",
      "INFO:tensorflow:global step 914: loss = 0.2012 (1.544 sec/step)\n",
      "INFO:tensorflow:global step 915: loss = 0.1637 (1.807 sec/step)\n",
      "INFO:tensorflow:global step 916: loss = 0.1635 (1.445 sec/step)\n",
      "INFO:tensorflow:global step 917: loss = 0.1632 (1.688 sec/step)\n",
      "INFO:tensorflow:global step 918: loss = 0.1628 (1.006 sec/step)\n",
      "INFO:tensorflow:global step 919: loss = 1.6473 (1.857 sec/step)\n",
      "INFO:tensorflow:global step 920: loss = 0.1639 (1.658 sec/step)\n",
      "INFO:tensorflow:global step 921: loss = 0.1772 (1.646 sec/step)\n",
      "INFO:tensorflow:global step 922: loss = 0.1711 (1.573 sec/step)\n",
      "INFO:tensorflow:global step 923: loss = 0.1763 (1.468 sec/step)\n",
      "INFO:tensorflow:global step 924: loss = 0.6584 (1.470 sec/step)\n",
      "INFO:tensorflow:global step 925: loss = 0.1775 (1.545 sec/step)\n",
      "INFO:tensorflow:global step 926: loss = 0.2522 (1.464 sec/step)\n",
      "INFO:tensorflow:global step 927: loss = 0.4590 (1.288 sec/step)\n",
      "INFO:tensorflow:global step 928: loss = 0.2541 (1.376 sec/step)\n",
      "INFO:tensorflow:global step 929: loss = 0.2872 (1.248 sec/step)\n",
      "INFO:tensorflow:global step 930: loss = 0.2056 (1.729 sec/step)\n",
      "INFO:tensorflow:global step 931: loss = 0.2856 (1.526 sec/step)\n",
      "INFO:tensorflow:global step 932: loss = 0.2448 (1.394 sec/step)\n",
      "INFO:tensorflow:global step 933: loss = 0.2295 (1.665 sec/step)\n",
      "INFO:tensorflow:global step 934: loss = 0.2432 (1.657 sec/step)\n",
      "INFO:tensorflow:global step 935: loss = 0.2260 (1.340 sec/step)\n",
      "INFO:tensorflow:global step 936: loss = 0.2138 (1.502 sec/step)\n",
      "INFO:tensorflow:global step 937: loss = 0.2213 (1.550 sec/step)\n",
      "INFO:tensorflow:global step 938: loss = 0.2171 (1.580 sec/step)\n",
      "INFO:tensorflow:global step 939: loss = 0.3273 (1.416 sec/step)\n",
      "INFO:tensorflow:global step 940: loss = 0.3176 (1.843 sec/step)\n",
      "INFO:tensorflow:global step 941: loss = 0.2534 (1.833 sec/step)\n",
      "INFO:tensorflow:global step 942: loss = 0.2752 (1.205 sec/step)\n",
      "INFO:tensorflow:global step 943: loss = 0.2265 (1.439 sec/step)\n",
      "INFO:tensorflow:global step 944: loss = 0.6575 (1.347 sec/step)\n",
      "INFO:tensorflow:global step 945: loss = 0.2235 (1.581 sec/step)\n",
      "INFO:tensorflow:global step 946: loss = 0.2322 (1.502 sec/step)\n",
      "INFO:tensorflow:global step 947: loss = 0.2764 (1.353 sec/step)\n",
      "INFO:tensorflow:global step 948: loss = 0.2644 (1.200 sec/step)\n",
      "INFO:tensorflow:global step 949: loss = 0.2338 (1.471 sec/step)\n",
      "INFO:tensorflow:global step 950: loss = 0.7382 (1.664 sec/step)\n",
      "INFO:tensorflow:global step 951: loss = 0.3127 (1.550 sec/step)\n",
      "INFO:tensorflow:global step 952: loss = 0.8075 (1.487 sec/step)\n",
      "INFO:tensorflow:global step 953: loss = 0.3365 (1.405 sec/step)\n",
      "INFO:tensorflow:global step 954: loss = 0.6473 (1.556 sec/step)\n",
      "INFO:tensorflow:global step 955: loss = 0.8550 (1.612 sec/step)\n",
      "INFO:tensorflow:global step 956: loss = 0.3210 (1.461 sec/step)\n",
      "INFO:tensorflow:global step 957: loss = 0.4656 (1.505 sec/step)\n",
      "INFO:tensorflow:global step 958: loss = 0.4171 (1.470 sec/step)\n",
      "INFO:tensorflow:global step 959: loss = 0.3961 (1.627 sec/step)\n",
      "INFO:tensorflow:global step 960: loss = 0.4007 (1.731 sec/step)\n",
      "INFO:tensorflow:global step 961: loss = 0.3186 (1.205 sec/step)\n",
      "INFO:tensorflow:global step 962: loss = 0.3347 (1.564 sec/step)\n",
      "INFO:tensorflow:global step 963: loss = 0.3391 (1.586 sec/step)\n",
      "INFO:tensorflow:global step 964: loss = 0.5859 (1.719 sec/step)\n",
      "INFO:tensorflow:global step 965: loss = 0.3026 (1.190 sec/step)\n",
      "INFO:tensorflow:global step 966: loss = 0.2851 (2.140 sec/step)\n",
      "INFO:tensorflow:global step 967: loss = 0.2699 (1.634 sec/step)\n",
      "INFO:tensorflow:global step 968: loss = 0.2815 (1.179 sec/step)\n",
      "INFO:tensorflow:global step 969: loss = 0.4786 (1.656 sec/step)\n",
      "INFO:tensorflow:global step 970: loss = 0.6860 (1.633 sec/step)\n",
      "INFO:tensorflow:global step 971: loss = 0.5752 (1.685 sec/step)\n",
      "INFO:tensorflow:global step 972: loss = 0.2623 (1.598 sec/step)\n",
      "INFO:tensorflow:global step 973: loss = 0.9435 (1.439 sec/step)\n",
      "INFO:tensorflow:global step 974: loss = 0.3057 (1.544 sec/step)\n",
      "INFO:tensorflow:global step 975: loss = 0.2943 (1.414 sec/step)\n",
      "INFO:tensorflow:global step 976: loss = 0.5792 (1.642 sec/step)\n",
      "INFO:tensorflow:global step 977: loss = 0.7606 (1.305 sec/step)\n",
      "INFO:tensorflow:global step 978: loss = 1.7755 (1.320 sec/step)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global step 979: loss = 0.6684 (1.303 sec/step)\n",
      "INFO:tensorflow:global step 980: loss = 0.8449 (1.798 sec/step)\n",
      "INFO:tensorflow:global step 981: loss = 0.8614 (1.428 sec/step)\n",
      "INFO:tensorflow:global step 982: loss = 0.8228 (1.438 sec/step)\n",
      "INFO:tensorflow:global step 983: loss = 0.6653 (1.499 sec/step)\n",
      "INFO:tensorflow:global step 984: loss = 1.4234 (1.427 sec/step)\n",
      "INFO:tensorflow:global step 985: loss = 1.0136 (1.365 sec/step)\n",
      "INFO:tensorflow:global step 986: loss = 1.0786 (1.393 sec/step)\n",
      "INFO:tensorflow:global step 987: loss = 1.0757 (1.428 sec/step)\n",
      "INFO:tensorflow:global step 988: loss = 0.8939 (1.260 sec/step)\n",
      "INFO:tensorflow:global step 989: loss = 0.7399 (1.594 sec/step)\n",
      "INFO:tensorflow:global step 990: loss = 1.6239 (1.463 sec/step)\n",
      "INFO:tensorflow:global step 991: loss = 0.8619 (1.737 sec/step)\n",
      "INFO:tensorflow:global step 992: loss = 0.7693 (1.672 sec/step)\n",
      "INFO:tensorflow:global step 993: loss = 2.8291 (1.242 sec/step)\n",
      "INFO:tensorflow:global step 994: loss = 0.7027 (1.165 sec/step)\n",
      "INFO:tensorflow:global step 995: loss = 2.5630 (1.278 sec/step)\n",
      "INFO:tensorflow:global step 996: loss = 0.6761 (1.566 sec/step)\n",
      "INFO:tensorflow:global step 997: loss = 1.0235 (1.355 sec/step)\n",
      "INFO:tensorflow:global step 998: loss = 1.9929 (1.035 sec/step)\n",
      "INFO:tensorflow:global step 999: loss = 1.7615 (1.488 sec/step)\n",
      "INFO:tensorflow:Stopping Training.\n",
      "INFO:tensorflow:Finished training! Saving model to disk.\n",
      "Finished training. Last batch loss 1.761539\n"
     ]
    }
   ],
   "source": [
    "# Note that this may take several minutes.\n",
    "\n",
    "import os\n",
    "\n",
    "from datasets import insulators\n",
    "from nets import inception\n",
    "from preprocessing import inception_preprocessing\n",
    "\n",
    "from tensorflow.contrib import slim\n",
    "image_size = inception.inception_v1.default_image_size\n",
    "\n",
    "insulators_data_dir = '/workspace/JiaXuejian'\n",
    "\n",
    "def get_init_fn():\n",
    "    \"\"\"Returns a function run by the chief worker to warm-start the training.\"\"\"\n",
    "    checkpoint_exclude_scopes=[\"InceptionV1/Logits\", \"InceptionV1/AuxLogits\"]\n",
    "    \n",
    "    exclusions = [scope.strip() for scope in checkpoint_exclude_scopes]\n",
    "\n",
    "    variables_to_restore = []\n",
    "    for var in slim.get_model_variables():\n",
    "        for exclusion in exclusions:\n",
    "            if var.op.name.startswith(exclusion):\n",
    "                break\n",
    "        else:\n",
    "            variables_to_restore.append(var)\n",
    "\n",
    "    return slim.assign_from_checkpoint_fn(\n",
    "      os.path.join(checkpoints_dir, 'inception_v1.ckpt'),\n",
    "      variables_to_restore)\n",
    "\n",
    "\n",
    "train_dir = '/tmp/inception_finetuned1/'\n",
    "\n",
    "with tf.Graph().as_default():\n",
    "    tf.logging.set_verbosity(tf.logging.INFO)\n",
    "    \n",
    "    dataset = insulators.get_split('train', insulators_data_dir)\n",
    "    images, _, labels = load_batch(dataset, height=image_size, width=image_size)\n",
    "    \n",
    "    # Create the model, use the default arg scope to configure the batch norm parameters.\n",
    "    with slim.arg_scope(inception.inception_v1_arg_scope()):\n",
    "        logits, _ = inception.inception_v1(images, num_classes=dataset.num_classes, is_training=True)\n",
    "        \n",
    "    # Specify the loss function:\n",
    "    one_hot_labels = slim.one_hot_encoding(labels, dataset.num_classes)\n",
    "    slim.losses.softmax_cross_entropy(logits, one_hot_labels)\n",
    "    total_loss = slim.losses.get_total_loss()\n",
    "\n",
    "    # Create some summaries to visualize the training process:\n",
    "    tf.summary.scalar('losses/Total Loss', total_loss)\n",
    "  \n",
    "    # Specify the optimizer and create the train op:\n",
    "    optimizer = tf.train.AdamOptimizer(learning_rate=0.01)\n",
    "    train_op = slim.learning.create_train_op(total_loss, optimizer)\n",
    "    \n",
    "    # Run the training:\n",
    "    final_loss = slim.learning.train(\n",
    "        train_op,\n",
    "        logdir=train_dir,\n",
    "        init_fn=get_init_fn(),\n",
    "        number_of_steps=1000)\n",
    "        \n",
    "  \n",
    "print('Finished training. Last batch loss %f' % final_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apply fine tuned model to some images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/python/util/tf_should_use.py:118: initialize_local_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.\n",
      "Instructions for updating:\n",
      "Use `tf.local_variables_initializer` instead.\n",
      "INFO:tensorflow:Restoring parameters from /tmp/inception_finetuned1/model.ckpt-1000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from datasets import insulators\n",
    "from nets import inception\n",
    "\n",
    "from tensorflow.contrib import slim\n",
    "\n",
    "insulators_data_dir = '/workspace/JiaXuejian'\n",
    "image_size = inception.inception_v1.default_image_size\n",
    "batch_size = 3\n",
    "\n",
    "with tf.Graph().as_default():\n",
    "    tf.logging.set_verbosity(tf.logging.INFO)\n",
    "    \n",
    "    dataset = insulators.get_split('train', insulators_data_dir)\n",
    "    images, images_raw, labels = load_batch(dataset, height=image_size, width=image_size)\n",
    "    \n",
    "    # Create the model, use the default arg scope to configure the batch norm parameters.\n",
    "    with slim.arg_scope(inception.inception_v1_arg_scope()):\n",
    "        logits, _ = inception.inception_v1(images, num_classes=dataset.num_classes, is_training=True)\n",
    "\n",
    "    probabilities = tf.nn.softmax(logits)\n",
    "    \n",
    "    checkpoint_path = tf.train.latest_checkpoint(train_dir)\n",
    "    init_fn = slim.assign_from_checkpoint_fn(\n",
    "      checkpoint_path,\n",
    "      slim.get_variables_to_restore())\n",
    "    \n",
    "    with tf.Session() as sess:\n",
    "        with slim.queues.QueueRunners(sess):\n",
    "            sess.run(tf.initialize_local_variables())\n",
    "            init_fn(sess)\n",
    "            np_probabilities, np_images_raw, np_labels = sess.run([probabilities, images_raw, labels])\n",
    "    \n",
    "            for i in range(batch_size): \n",
    "                image = np_images_raw[i, :, :, :]\n",
    "                true_label = np_labels[i]\n",
    "                predicted_label = np.argmax(np_probabilities[i, :])\n",
    "                predicted_name = dataset.labels_to_names[predicted_label]\n",
    "                true_name = dataset.labels_to_names[true_label]\n",
    "                \n",
    "                plt.figure()\n",
    "                plt.imshow(image.astype(np.uint8))\n",
    "                plt.title('Ground Truth: [%s], Prediction [%s]' % (true_name, predicted_name))\n",
    "                plt.axis('off')\n",
    "                plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
